REU Site: Computational Methods with applications in Materials Science

点击翻译按钮获取中文摘要

NON-TECHNICAL SUMMARY: Computational methods and data analysis are now widely used to predict the properties of materials and to understand data from materials experiments and simulations. While these computational techniques are commonly taught in graduate programs in science, math, and engineering, few undergraduate students have an opportunity to learn about them or participate in this rapidly expanding research field. Jointly funded by the Division of Materials Research and the Established Program to Stimulate Competitive Research (EPSCoR), this Research Experiences for Undergraduates (REU) site addresses this shortcoming and provides a unique opportunity for undergraduate participants to participate in meaningful research with a group of researchers from the Center for Computational Sciences (CCS), an interdisciplinary computational research center at Mississippi State University (MSU). Participants will spend ten weeks at MSU performing research mentored by faculty from Physics, Chemistry, Mathematics and Statistics, and Engineering. In addition to hands-on research experience, participants will attend weekly seminars and workshops covering topics related to computation, materials, and career development. A significant portion of participants for this REU project are recruited from historically black colleges and universities and primarily undergraduate institutions from across the United States. Graduates of this REU site will be well prepared for graduate study in science, engineering, or mathematics.TECHNICAL SUMMARY: The student participants recruited for this REU spend 10 weeks over the summer in multidisciplinary research with faculty mentors in Mathematics, Statistics, Physics, Chemistry, and Engineering from the CCS. The students are first trained in the basic science and computational techniques necessary for their research projects. Additional training activities improve the participants’ computational skills and written and oral presentation skills. The research projects fall into two general areas: materials simulation and design, and computational data analysis applied to materials. Specific projects include (1) modeling of superfluorescence; (2) electron-electron correlation; (3) machine learning prediction of interatomic forces; (4) multifunctional materials design; (5) numerical methods for time-dependent problems; (6) simulation and design of self-assembled gels; (7) optical properties of polycyclic aromatic hydrocarbons; (8) continuous data assimilation; (9) image denoising and segmentation; and (10) high-dimensional data analysis. REU participants are given access to supercomputing resources at the MSU High Performance Computing Collaboratory. The students participate in the weekly group meetings, seminars and training sessions on scientific and computational topics. At the end of the summer, they present the final results of their project to the REU group and at the MSU Summer Undergraduate Research Symposium.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.